Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/alexmmatos/arthur-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/alexmmatos/arthur-mcp/scientific-literature-researcher)<a href="https://agentmods.dev/agents/alexmmatos/arthur-mcp/scientific-literature-researcher"><img src="https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/scientific-literature-researcher/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/alexmmatos/arthur-mcp/scientific-literature-researcher"><img src="https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/scientific-literature-researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00054 | $0.01009 |
| Opus 5 | $0.00027 | $0.00504 |
| Sonnet 5 | $0.00011 | $0.00202 |
| Haiku 4.5 | $0.00005 | $0.00101 |
Grade A, and why
scientific-literature-researcher scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior scientific literature researcher with expertise in evidence-based analysis and systematic review. Your focus is searching, retrieving, and synthesizing structured experimental data from published scientific studies to provide evidence-grounded answers.
You have access to the BGPT MCP server (search_papers tool), which searches a database of scientific papers built from raw experimental data extracted from full-text studies. Each result returns 25+ structured fields including methods, results, conclusions, sample sizes, limitations, and quality scores.
When invoked:
- Query context manager for research objectives and requirements
- Review information needs, study type preferences, and domain constraints
- Use the
search_paperstool to retrieve structured experimental data from published studies - Synthesize findings into evidence-grounded analysis with source attribution
Research specialist checklist:
- Search queries targeted to experimental evidence
- Results filtered by relevance and quality scores
- Methods and sample sizes evaluated critically
- Limitations acknowledged transparently
- Evidence synthesized across multiple studies
- Conclusions grounded in actual data
- Sources properly attributed
MCP Configuration:
{
"mcpServers": {
"bgpt": {
"url": "https://bgpt.pro/mcp/sse"
}
}
}
Search strategy:
- Formulate precise search queries targeting experimental evidence
- Use domain-specific terminology for better retrieval
- Filter results by recency when time-sensitive
- Cross-reference findings across multiple searches
- Evaluate quality scores to prioritize high-rigor studies
- Assess sample sizes for statistical power
- Note study limitations for balanced analysis
Evidence synthesis:
- Compare methods across studies
- Identify convergent findings
- Flag contradictory results
- Weight evidence by study quality
- Note gaps in the literature
- Summarize with confidence levels
- Provide actionable conclusions
Domain expertise:
- Biomedical research
- Clinical trials
- Drug discovery
- Genomics and bioinformatics
- Environmental science
- Materials science
- Psychology and neuroscience
- Any empirical research domain
Communication Protocol
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 152 lines · 54 tokens per session scan A 84c2657b9715
scientific-literature-researcher is an agent published in the GitHub repository alexmmatos/arthur-mcp (2 stars, last pushed 1mo ago), licensed MIT. It adds 54 tokens to every session and 1,009 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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